code: def test_add_indicators_to_one_variable(df_na):
      imputer = AddMissingIndicator(variables="Name")
      X_transformed = imputer.fit_transform(df_na)
      assert imputer.variables_ == ["Name"]
      assert X_transformed.shape == (8, 7)
      assert "Name_na" in X_transformed.columns
      assert X_transformed["Name_na"].sum() == 2
  
file_path: feature_engine/tests/test_imputation/test_missing_indicator.py
imports: import pytest
  from sklearn.pipeline import Pipeline
  from feature_engine.imputation import AddMissingIndicator
label_desc: Use image node_id 3 for calling a global function with example usage: test_add_indicators_to_one_variable(df_na) without return types